CIO Business Intelligence

OCTOBER 13, 2023

Application data architect: The application data architect designs and implements data models for specific software applications. Information/data governance architect: These individuals establish and enforce data governance policies and procedures.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

IBM Big Data Hub

OCTOBER 30, 2023

IBM, a pioneer in data analytics and AI, offers watsonx.data, among other technologies, that makes possible to seamlessly access and ingest massive sets of structured and unstructured data. The retailer uses these insights to optimize inventory levels, reduce costs and enhance efficiency.

Insurance 78

Insurance Data Warehouse Data-driven Unstructured Data 78

CIO Business Intelligence

DECEMBER 11, 2023

Focus on an administrative operation that is expensive, currently relies on heavy manual activity, and is hindered by a large amount of unstructured data. Other options include using generative AI to support clinical summarization work, referral management, or to optimize your supply chain.

Unstructured Data 75

Unstructured Data Interactive Data-driven Consulting 75

IBM Big Data Hub

MAY 14, 2024

A generative AI agent or assistant can ingest and summarize structured and unstructured data from internal and external sources, parse through it and generate insights and patterns for financial information that can drive business value and potentially identify untapped revenue streams.

Finance 68

Finance Cost-Benefit Reporting Forecasting 68

Cloudera

JANUARY 28, 2022

Then there are the more extensive discussions – scrutiny of the overarching, data strategy questions related to privacy, security, data governance /access and regulatory oversight. These are not straightforward decisions, especially when data breaches always hit the top of the news headlines.

Slice and Dice 115

Slice and Dice Cost-Benefit Risk Data Governance 115

Alation

JUNE 2, 2022

In part one of this series, I discussed how data management challenges have evolved and how data governance and security have to play in such challenges, with an eye to cloud migration and drift over time. A data catalog is a central hub for XAI and understanding data and related models. Other Technologies.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

IBM Big Data Hub

DECEMBER 16, 2022

Meanwhile, the company’s IT teams could optimize their time by focusing on other important workloads. Comprehensive search and access to relevant data. Because Alex can use a data catalog to search all data assets across the company, she has access to the most relevant and up-to-date information.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

erwin

JUNE 26, 2020

It’s no surprise that most organizations’ data is often fragmented and siloed across numerous sources (e.g., legacy systems, data warehouses, flat files stored on individual desktops and laptops, and modern, cloud-based repositories.). This also diminishes the value of data as an asset.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

IBM Big Data Hub

JANUARY 5, 2023

Meaning, data architecture is a foundational element of your business strategy for higher data quality. Perform data quality monitoring based on pre-configured rules. Decide on the changes that will optimize your data for achieving your business objectives.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

Laminar Security

AUGUST 21, 2023

The Hype Cycle for Data Security Gartner’s Hype Cycle for Data Security, 2023 covers various aspects of data security that leaders must review based on their risk appetite and data storage, processing, and access practices. Organizations should assess integration capabilities and standardize remediation processes.

Management 40

Management Risk Unstructured Data Data Strategy 40

AWS Big Data

JULY 19, 2023

We’ve seen that there is a demand to design applications that enable data to be portable across cloud environments and give you the ability to derive insights from one or more data sources. With this connector, you can bring the data from Google Cloud Storage to Amazon S3.

Big Data 83

Big Data Software Consulting Unstructured Data 83

AWS Big Data

OCTOBER 20, 2023

We’ve seen a demand to design applications that enable data to be portable across cloud environments and give you the ability to derive insights from one or more data sources. With these connectors, you can bring the data from Azure Blob Storage and Azure Data Lake Storage separately to Amazon S3. Learn more in README.

Data Lake 84

Data Lake Big Data Consulting Data Warehouse 84

Cloudera

SEPTEMBER 7, 2018

Moreover, this approach struggles to deal with the large volume and variety of data that must be analyzed and often correlated. Analyzing unstructured data sets such as text, audio and images are challenging, especially while determining illegal intent in communications. Requirements for data protection and governance .

Machine Learning 49

Machine Learning Risk Unstructured Data Cost-Benefit 49

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 102

Data Lake Sales Data Warehouse Snapshot 102

BizAcuity

APRIL 14, 2022

With the amount of data being accumulated, it is easier when said. There are a wide range of problems that are presented to organizations when working with big data. Challenges associated with Data Management and Optimizing Big Data. Unscalable data architecture. Unstructured Data Management.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

DataKitchen

APRIL 13, 2021

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Monte Carlo Data — Data reliability delivered. Data breaks. Process Analytics. Meta-Orchestration .

Testing 300

Testing Machine Learning Consulting Data Quality 300

AWS Big Data

APRIL 19, 2023

In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments. However, these wide-ranging data types are typically stored in silos across multiple data stores.

Data Warehouse 55

Data Warehouse Data Lake Unstructured Data Optimization 55

IBM Big Data Hub

MAY 9, 2023

IBM today announced it is launching IBM watsonx.data , a data store built on an open lakehouse architecture, to help enterprises easily unify and govern their structured and unstructured data, wherever it resides, for high-performance AI and analytics. What is watsonx.data?

Data Warehouse 73

Data Warehouse Cost-Benefit Recreation/Entertainment Unstructured Data 73

IBM Big Data Hub

JANUARY 17, 2023

Essential components of a data lakehouse architecture and what makes an open data lakehouse. At the core of a data lakehouse architecture includes the storage, metadata service and the query engine, and typically a data governance component made up of a policy engine and a data dictionary.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Alation

MARCH 21, 2023

To fully realize data’s value, organizations in the travel industry need to dismantle data silos so that they can securely and efficiently leverage analytics across their organizations. What is big data in the travel and tourism industry? What are common data challenges for the travel industry?

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

Cloudera

JULY 29, 2022

Telecom operators can gain a competitive advantage by leveraging the massive volume of data generated on their networks. They can outperform competitors by applying machine learning and artificial intelligence to understand and optimize the customer experience while aiding service assurance.

Data Architecture 89

Data Architecture Data Strategy Risk Management Strategy 89

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. To build a SQL query, one must describe the data sources involved and the high-level operations (SELECT, JOIN, WHERE, etc.)

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

AWS Big Data

JUNE 9, 2023

Data in customers’ data lakes is used to fulfil a multitude of use cases, from real-time fraud detection for financial services companies, inventory and real-time marketing campaigns for retailers, or flight and hotel room availability for the hospitality industry.

Data Lake 113

Data Lake Metadata Optimization Statistics 113

erwin

JUNE 27, 2019

The need for an effective data modeling tool is more significant than ever. For decades, data modeling has provided the optimal way to design and deploy new relational databases with high-quality data sources and support application development. Other considerations include the ability to: Compare models and databases.

Measurement 81

Measurement Modeling Unstructured Data Metadata 81

Grooper

AUGUST 19, 2019

Master data management. Data governance. Structured, semi-structured, and unstructured data. Data pipelines. A classic example often cited is John Deere’s innovative investment in a new way of optimizing inventory called “direct de rivative estimation of non-stationary inventory.” Primary keys.

Analytics 54

Analytics Machine Learning Data Science Data-driven 54

CIO Business Intelligence

AUGUST 1, 2023

But with all the excitement and hype, it’s easy for employees to invest time in AI tools that compromise confidential data or for managers to select shadow AI tools that haven’t been through security, data governance, and other vendor compliance reviews.

Digital Transformation 98

Digital Transformation Unstructured Data Strategy Experimentation 98

datapine

FEBRUARY 22, 2022

In the article, he pointed to a pretty fascinating trend: “Experian has predicted that the CDO position will become a standard senior board-level role by 2020, bringing the conversation around data gathering, management, optimization, and security to the C-level.” We love that data is moving permanently into the C-Suite.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

Alation

FEBRUARY 10, 2022

Let’s discuss what data classification is, the processes for classifying data, data types, and the steps to follow for data classification: What is Data Classification? Either completed manually or using automation, the data classification process is based on the data’s context, content, and user discretion.

Data Governance 52

Data Governance Risk Insurance Metadata 52

Alation

NOVEMBER 22, 2022

What Is Data Governance In The Public Sector? Effective data governance for the public sector enables entities to ensure data quality, enhance security, protect privacy, and meet compliance requirements. With so much focus on compliance, democratizing data for self-service analytics can present a challenge.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

Cloudera

OCTOBER 7, 2021

Infrastructure Environment: The infrastructure (including private cloud, public cloud or a combination of both) that hosts application logic and data. The Data Governance body designates a Data Product as the Authoritative Data Source (ADS) and its Data Publisher as the Authoritative Provisioning Point (APP).

Metadata 124

Metadata Cost-Benefit Enterprise Interactive 124

erwin

MARCH 26, 2020

As a result, we’re seeing the rise of the “citizen analyst,” who brings business knowledge and subject-matter expertise to data-driven insights. Some examples of citizen analysts include the VP of finance who may be looking for opportunities to optimize the top- and bottom-line results for growth and profitability.

Data-driven 90

Data-driven Unstructured Data Enterprise Finance 90

IBM Big Data Hub

AUGUST 4, 2023

Data democratization instead refers to the simplification of all processes related to data, from storage architecture to data management to data security. It also requires an organization-wide data governance approach, from adopting new types of employee training to creating new policies for data storage.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

Alation

APRIL 19, 2022

Data modernization is the process of transferring data to modern cloud-based databases from outdated or siloed legacy databases, including structured and unstructured data. In that sense, data modernization is synonymous with cloud migration. What Is the Role of the Cloud in Data Modernization?

Cost-Benefit 52

Cost-Benefit Data Governance Manufacturing Data Architecture 52

AWS Big Data

JULY 28, 2023

Considerations Note the following considerations: The Data Catalog auto-mount provides ease of use to analysts or database users. The security setup (setting up the permissions model or data governance) is owned by account and database administrators.

Data Lake 67

Data Lake Data Governance Data Warehouse Modeling 67

Laminar Security

MAY 3, 2023

They define DSPM technologies this way: “DSPM technologies can discover unknown data and categorize structured and unstructured data across cloud service platforms. This accessibility of data is vital to business growth, but has also resulted in a significant increase in risk.

Management 52

Management Risk Risk Management Data Processing 52